XPost: comp.ai.neural-nets, sci.stat.consult   
   From: krishna.1234.k@gmail.com   
      
   I have some data which belongs to a category (say cooking appliances),   
   I would like to extract various attributes (e.g.,oven-safe, heat-   
   resistant, size) applicable for that data. My approach is to get the   
   most occurring patterns in the data and look at the top patterns   
   manually and determine the attributes (e.g., inches, cms indicate   
   size). Can I please know some (if any) well known algorithms that can   
   be useful for this job, I have read that Naive-bayes,  Support Vector   
   Machines etc are used for classifying data and that they use some   
   training data (which is already classified) to determine the   
   classification criteria, I am not sure if and how these methods can be   
   used for my task. I would appreciate suggestions on various   
   approaches. I guess I can say that the answer I am looking is about   
   automatic text classification.   
      
   Thanks,   
   Krishna   
      
   PS. This is NOT my homework assignment :)   
      
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